diff --git a/resumes/build/mnisyif_resume.pdf b/resumes/build/mnisyif_resume.pdf index f7aa6b9..41f1724 100644 Binary files a/resumes/build/mnisyif_resume.pdf and b/resumes/build/mnisyif_resume.pdf differ diff --git a/resumes/mnisyif_resume.tex b/resumes/mnisyif_resume.tex index 6dc443b..74dd1cf 100644 --- a/resumes/mnisyif_resume.tex +++ b/resumes/mnisyif_resume.tex @@ -122,106 +122,98 @@ %----------HEADING---------- \begin{tabular*}{\textwidth}{@{\hspace{-1ex}}l} - \textbf{\href{http://m.nisyif.com/}{\Huge\color{blue}MURTADHA NISYIF}} \vspace{2pt}\\ - \href{mailto:mnisyif@gmail.com}{\faIcon{at} mnisyif@gmail.com} $|$ - \faIcon{phone-square-alt} +1 (519) 502-8463 $|$ - \faIcon{map-marker-alt} Ontario, Canada $|$ - \href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$ - \href{https://www.linkedin.com/in/mnisyif}{\faIcon{linkedin} linkedin.com/ln/mnisyif} $|$ - \href{https://github.com/mnisyif}{\faIcon{github} github.com/mnisyif}\vspace{12pt} \\ + \textbf{\href{http://m.nisyif.com/}{\Huge\color{blue}MURTADHA NISYIF}} \vspace{2pt}\\ + \href{mailto:mnisyif@gmail.com}{\faIcon{at} mnisyif@gmail.com} $|$ + \faIcon{phone-square-alt} +964 775 608 4424 $|$ + \faIcon{map-marker-alt} Karbala, Iraq $|$ + \href{https://m.nisyif.com/}{\faIcon{user-tie} m.nisyif.com} $|$ + \href{https://www.linkedin.com/in/mnisyif}{\faIcon{linkedin} linkedin.com/ln/mnisyif} $|$ + \href{https://github.com/mnisyif}{\faIcon{github} github.com/mnisyif}\vspace{12pt} \\ \end{tabular*} \vspace{-20pt} %-----------SUMMARY---------- \section{\color{blue}SUMMARY} - Versatile computer engineer and researcher specialized in \textbf{Semantic Communications}. - Explored and implemented methods to optimize AI-driven communication by extracting and transmitting only \textbf{task-critical "meaningful features"} rather than raw pixel data. - This approach enables autonomous systems to maintain high intelligence and operational reliability over congested or weak network environments. +Versatile Computer Engineer and Researcher specialized in Semantic Communications and Edge Computing. First author of two IEEE conference papers focused on optimizing edge-cloud communication through task-driven feature extraction. \textbf{Bilingual in English and Arabic}, with expertise in developing high-efficiency AI pipelines for 5G/6G and Smart City infrastructure. Proven track record of reducing bandwidth demand by \textbf{30$\times$} while maintaining 96\% task accuracy in congested network environments. + +\vspace{-7pt} - \vspace{-7pt} %-----------EDUCATION----------- \section{\color{blue}EDUCATION} - \resumeSubHeadingListStart - \resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{Dec 2025} - \resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{Apr 2023} - \resumeSubHeadingListEnd +\resumeSubHeadingListStart +\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{MASc. - Computer Engineering}}{Dec 2025} +\resumeSchoolItem{University of Guelph $|$ \color{blue} \emph{B.Eng. - Computer Engineering}}{Apr 2023} +\resumeSubHeadingListEnd % \vspace{-8pt} %-----------SKILLS----------- \section{\color{blue}CERTIFICATIONS, SKILLS, TECHNOLOGIES, INTERESTS} - \begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X } - \textbf{Certifications: } & AWS Solutions Architect\\ - \textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\ - \textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash\\ - \textbf{Tech Stacks: } & FastAPI; PyTorch; React; Flask; SQLite; PostgresSQL; NumPy; SciPy; Scikit-learn; Matplotlib; MongoDB; Docker; Git; Jenkins; Terraform; AWS; Kubernetes; Express JS; Node.js; Swagger\\ - \textbf{Languages: } & English (Fluent); Arabic (Fluent) - \end{tabularx} - \vspace{-7pt} +\begin{tabularx}{\textwidth}{ @{} >{\bfseries}l X } + % \textbf{Certifications: } & AWS Solutions Architect\\ + \textbf{Skills: } & AI; DevOps; Cloud Computing; IaC; Containerization; CI/CD; Monitoring; Data Engineering; ML Ops \\ + \textbf{Languages: } & Python; C++; C; JavaScript; Rust; HTML; Java; Bash \\ + \textbf{Tech Stacks: } & FastAPI; PyTorch; React; Flask; SQLite; PostgresSQL; NumPy; SciPy; Scikit-learn; Matplotlib; MongoDB; Docker; Git; Jenkins; Terraform; AWS; Kubernetes; Express JS; Node.js; Swagger \\ +\end{tabularx} +\vspace{-7pt} %----------Experience---------- \section{\color{blue}WORK EXPERIENCE} - \resumeSubHeadingListStart - \resumeSubheading - {Researcher - Machine Learning \& Semantic Communications}{Jan 2024 – Dec 2025} - {University of Guelph}{ Guelph, Ontario} - \resumeItemListStart - \resumeItem {Developed semantic communication pipelines using Swin Transformer models, achieving a 30× reduction in bandwidth usage and 29\% lower latency while preserving atleast 96\% task accuracy under variable network conditions} - \resumeItem {Extended models with adaptive deterministic mechanisms to handle bandwidth fluctuations and anomalies, ensuring stable real-time performance} - \resumeItem {Quantized encoder models to INT8 during edge–cloud simulations to emulate smartphone hardware constraints (6-core CPU, limited RAM), enabling realistic performance benchmarking} - \resumeItem {Published a first-author paper in IEEE conference proceedings, detailing the novel integration of semantic communication with edge computing for real-time, near real-time and task-offloading applications} - \resumeItemListEnd +\resumeSubHeadingListStart +\resumeSubheading +{Researcher - Machine Learning \& Semantic Communications}{Jan 2024 – Dec 2025} +{University of Guelph}{ Guelph, Ontario} +\resumeItemListStart +\resumeItem {Developed semantic communication pipelines using Swin Transformer models, achieving a 30× reduction in bandwidth usage and 29\% lower latency while preserving atleast 96\% task accuracy under variable network conditions} +\resumeItem {Extended models with adaptive deterministic mechanisms to handle bandwidth fluctuations and anomalies, ensuring stable real-time performance} +\resumeItem {Quantized encoder models to INT8 during edge–cloud simulations to emulate smartphone hardware constraints (6-core CPU, limited RAM), enabling realistic performance benchmarking} +\resumeItem {Published a first-author paper in IEEE conference proceedings, detailing the novel integration of semantic communication with edge computing for real-time, near real-time and task-offloading applications} +\resumeItemListEnd - \resumeSubheading - {Software Developer}{Oct 2022 – Oct 2023} - {University of Guelph – Robotics Institute}{ Guelph, Ontario} - \resumeItemListStart - \resumeItem {Architected and containerized a multi-technology stack combining ROS2, Node.js, and Vue to enable seamless real-time control across distributed robotic systems} - \resumeItem {Implemented automated AWS infrastructure provisioning with Terraform and integrated CI/CD pipelines via GitLab and Jenkins, reducing manual deployment steps by 80\%} - \resumeItem {Created a secure certificate management workflow that streamlined Let's Encrypt renewals and configured a Nginx reverse proxy to enforce HTTPS and granular CORS policies} - \resumeItem {Led the design and implementation of an accessible smart door system using ESP32, PIR sensors, and React Native, achieving over 95\% reliability in extensive field tests} - \resumeItemListEnd +\resumeSubheading +{Software Developer}{Oct 2022 – Oct 2023} +{University of Guelph - Robotics Institute}{ Guelph, Ontario} +\resumeItemListStart +\resumeItem {Architected and containerized a multi-technology stack combining ROS2, Node.js, and Vue to enable seamless real-time control across distributed robotic systems} +\resumeItem {Implemented automated AWS infrastructure provisioning with Terraform and integrated CI/CD pipelines via GitLab and Jenkins, reducing manual deployment steps by 80\%} +\resumeItem {Created a secure certificate management workflow that streamlined Let's Encrypt renewals and configured a Nginx reverse proxy to enforce HTTPS and granular CORS policies} +\resumeItem {Led the design and implementation of an accessible smart door system using ESP32, PIR sensors, and React Native, achieving over 95\% reliability in extensive field tests} +\resumeItemListEnd - \resumeSubheading - {Information Technology Analyst}{Jul 2020 – Dec 2020} - {Kitchener Downtown Community Health Center — SRHC}{ Kitchener, Ontario} - \resumeItemListStart - \resumeItem {Deployed and tuned a centralized Samba file server, increasing file distribution efficiency by 40\% across more than 20 staff and multiple departments} - \resumeItem {Configured and maintained a FortiGate firewall and VPN solution for 60 users, integrating Prometheus-based monitoring for real-time diagnostics and rapid issue resolution} - \resumeItemListEnd +\resumeSubheading +{Information Technology Analyst}{Jul 2020 – Dec 2020} +{Kitchener Downtown Community Health Center - SRHC}{ Kitchener, Ontario} +\resumeItemListStart +\resumeItem {Deployed and tuned a centralized Samba file server, increasing file distribution efficiency by 40\% across more than 20 staff and multiple departments} +\resumeItem {Configured and maintained a FortiGate firewall and VPN solution for 60 users, integrating Prometheus-based monitoring for real-time diagnostics and rapid issue resolution} +\resumeItemListEnd - \resumeSubHeadingListEnd +\resumeSubHeadingListEnd %-----------PROJECTS----------- \section{\color{blue}PROJECTS} - \resumeSubHeadingListStart +\resumeSubHeadingListStart - % \resumeProjectHeading {\textbf{\color{black}Personal Portfolio Website} $|$ \color{blue} \emph{React, Rust, Async, Jenkins, Docker}}{} - % \resumeItemListStart - % \resumeItem{Built a portfolio website featuring a React frontend coupled with a resilient Rust backend} - % \resumeItem{Integrated comprehensive Jenkins CI/CD pipelines and Docker-based deployment, slashing manual release efforts by 70\% and ensuring high availability} - % \resumeItemListEnd +\resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{} +\resumeItemListStart +\resumeItem{Orchestrate a comprehensive home lab environment managing 15+ Docker containers for media, web, and gaming services, configured auto-renewal SSL/TLS certification with Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics} +\resumeItemListEnd - \resumeProjectHeading {\textbf{\color{black}Home lab Adminstration} $|$ \color{blue} \emph{Docker, Terraform, Jenkins, Prometheus, Grafana, SSL/TLS}}{} - \resumeItemListStart - \resumeItem{Orchestrate a comprehensive home lab environment managing 15+ Docker containers for media, web, and gaming services, configured auto-renewal SSL/TLS certification with Let’s Encrypt, setup Prometheus/Grafana monitoring, and applied Fail2Ban for robust security achieving 99.9\% uptime and detailed system analytics} - \resumeItemListEnd +\resumeProjectHeading{\textbf{\color{black}HAM10K Skin Cancer Classifier} $|$ \color{blue} \emph{Python, PyTorch, SciPy, Pandas}}{} +\resumeItemListStart +\resumeItem{Engineered a comprehensive deep learning pipeline integrating a PCA-enhanced MLP, a custom-designed DCNN, and the RegNetY-320 architecture} +\resumeItem{Applied systematic class rebalancing and extensive data augmentation to achieve 96.9\% accuracy, an optimal F1-score, and a flawless 1.00 AUC} +\resumeItemListEnd - \resumeProjectHeading{\textbf{\color{black}HAM10K Skin Cancer Classifier} $|$ \color{blue} \emph{Python, PyTorch, SciPy, Pandas}}{} - \resumeItemListStart - \resumeItem{Engineered a comprehensive deep learning pipeline integrating a PCA-enhanced MLP, a custom-designed DCNN, and the RegNetY-320 architecture} - \resumeItem{Applied systematic class rebalancing and extensive data augmentation to achieve 96.9\% accuracy, an optimal F1-score, and a flawless 1.00 AUC} - \resumeItemListEnd +\resumeProjectHeading{\textbf{\color{black}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{} +\resumeItemListStart +\resumeItem{Developed a scalable Flask-RESTful API paired with an interactive HTML/JS frontend while leveraging the UCI dataset and implemented real-time feature scaling with hyperparameter tuning to deliver a 95\% prediction accuracy, supporting timely clinical decision-making} +\resumeItemListEnd - \resumeProjectHeading{\textbf{\color{black}Heart Disease Predictor} $|$ \color{blue} \emph{Python, Flask, RESTful, HTML, CSS, JS}}{} - \resumeItemListStart - \resumeItem{Developed a scalable Flask-RESTful API paired with an interactive HTML/JS frontend while leveraging the UCI dataset and implemented real-time feature scaling with hyperparameter tuning to deliver a 95\% prediction accuracy, supporting timely clinical decision-making} - \resumeItemListEnd - - \resumeProjectHeading{\textbf{\color{black} Real-Time Noise Cancellation with RL} $|$ \color{blue} \emph{Python, PyTorch, Gymnasium, SciPy, librosa}}{} - \resumeItemListStart - \resumeItem{Created a bespoke OpenAI Gym environment incorporating FFT-based audio processing and trained a PPO agent to perform adaptive noise cancellation in real time, achieving processing speeds exceeding 5,200 FPS for high-fidelity audio performance} - \resumeItemListEnd - \resumeSubHeadingListEnd - % \vspace{-8pt} +\resumeProjectHeading{\textbf{\color{black} Real-Time Noise Cancellation with RL} $|$ \color{blue} \emph{Python, PyTorch, Gymnasium, SciPy, librosa}}{} +\resumeItemListStart +\resumeItem{Created a bespoke OpenAI Gym environment incorporating FFT-based audio processing and trained a PPO agent to perform adaptive noise cancellation in real time, achieving processing speeds exceeding 5,200 FPS for high-fidelity audio performance} +\resumeItemListEnd +\resumeSubHeadingListEnd +% \vspace{-8pt} \end{document}